Graphic visualizations are often used for displaying images, diagrams, animations, and the like, to communicate a meaningful understanding of data through visual imagery. Visualizations can be in the form of plots, graphs, charts, diagrams, drawings, and the like, and can be used to represent underlying data in some form that can be understood by a viewer. Some data types can be more difficult to efficiently display through visualizations. For example, hierarchical data is a data model in which data is organized in a hierarchical format (e.g., a tree structure, etc.) Many current databases store records in the form of a hierarchical database model. In this model, records and their attributes may be connected to one another through links. Each record may include a collection of fields and each field may include one or more values. This type of data structure is beneficial because it is simple and rigid and can be traversed quickly with a processing device, etc.
However, databases are often tasked with storing thousands or even millions of records where each record includes multiple fields and values of data. As a result, visually representing complex scenarios of hierarchically linked information can be a difficult task, if not impractical. Furthermore, identifying context from within thousands of database records can also be difficult. Accordingly, what is needed is technology that can provide visualizations of hierarchical data in a format that is understandable and efficient for viewing complex scenarios.
Throughout the drawings and the detailed description, unless otherwise described, the same drawing reference numerals will be understood to refer to the same elements, features, and structures. The relative size and depiction of these elements may be exaggerated or adjusted for clarity, illustration, and/or convenience.